Results for “active data” — Page 39

DOE OSTI2021

A reporting format for field measurements of soil respiration

Field observations of the soil-to-atmosphere CO2 flux–soil respiration, RS–are a prime example of ‘long tail’ data that historically have had neither centralized databases nor an agreed-upon reporting format. This has hindered scientific transparency, analytical reproducibility, and novel syntheses with respect to this globally-important component of the carbon cycle. Here we propose a new data and metadata reporting format for RS data, based on engagement with a wide range of researchers in the field as well as expert advisory panels. Our goal was a reporting format that would be relevant and useful for synthesis activities, and optimizing data discoverability and usability while not placing an undue burden on data contributors. We describe previous RS data collection efforts, lessons learned from related databases and data-oriented networks (e.g. FLUXNET) in earth and ecological sciences, and the process of community consultation. The proposed reporting format focuses on chamber-level data and metadata, specifying measurement conditions and, for a given measurement period defined by beginning and ending timestamps, a mean RS flux (or CO2 concentration) and associated ancillary measurements. Fundamentally, this format aims to enable findable, accessible, interoperable, and reusable data, while providing ‘future-proofing’ capabilities to support reanalyses using as yet unknown algorithms or approaches. Finally, this proposed RS reporting format is available online, and is intended to be a dynamic document, subject to further community feedback and/or change in the future.

Bond-Lamberty, Benjamin↗

DOE OSTI2016

NCSP Nuclear Data Advisory Group (NDAG) Report

We review Nuclear Data Advisory Group activities during FY15.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

ARM Data for Examining the Ice-Nucleating Particles from SGP Part II (ExINP-SGP II) Gas Adsorption Analyzer

Knowledge of airborne particulate matter (PM), especially the particles that have supermicron diameters, is key for understanding ice-nucleating particles (INPs). Supported by the Atmospheric Radiation Measurement (ARM) user facility, we sampled PM and surface soil materials at the Southern Great Plains observatory (SGP; 36° 36′ 18″ N, 97° 29′ 6″ W) to systematically compare the INP abundance and ice nucleation efficiency of different SGP samples (i.e., airborne versus surface materials). The field campaign, named Examing INP from SGP II (ExINP-SGP II), was conducted from 20 January to 20 April, 2021. Our data analysis products include (1) physical surface sorption characterization data (i.e., BET, pore volume) of two sets of samples -- SGP Soil and USDA, (2) X-ray diffraction spectra for the same two samples, (3) immersion freezing assay-based ice nucleation active mass density data as a function of freezing temperature for both ambient and surface samples, and (4) time-series data of ambient meteorological conditions, concentration particle counter-derived aerosol particle concentration, and aerosol particle sizer measurement during ExINP-SGP II.

3Flex,BET specific surface area and pore volume, A↗

DOE OSTI2021

ARM Data for Examining the Ice-Nucleating Particles from SGP Part II (ExINP-SGP II) X-Ray Diffraction

Knowledge of airborne particulate matter (PM), especially the particles that have supermicron diameters, is key for understanding ice-nucleating particles (INPs). Supported by the Atmospheric Radiation Measurement (ARM) user facility, we sampled PM and surface soil materials at the Southern Great Plains observatory (SGP; 36° 36′ 18″ N, 97° 29′ 6″ W) to systematically compare the INP abundance and ice nucleation efficiency of different SGP samples (i.e., airborne versus surface materials). The field campaign, named Examing INP from SGP II (ExINP-SGP II), was conducted from 20 January to 20 April, 2021. Our data analysis products include (1) physical surface sorption characterization data (i.e., BET, pore volume) of two sets of samples -- SGP Soil and USDA, (2) X-ray diffraction spectra for the same two samples, (3) immersion freezing assay-based ice nucleation active mass density data as a function of freezing temperature for both ambient and surface samples, and (4) time-series data of ambient meteorological conditions, concentration particle counter-derived aerosol particle concentration, and aerosol particle sizer measurement during ExINP-SGP II.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

ARM Data for Examining the Ice-Nucleating Particles from SGP Part II (ExINP-SGP II) Aerodynamic Particle Sizer, Condensation Particle Counter, and Meteorological Instrument Data Analysis

Knowledge of airborne particulate matter (PM), especially the particles that have supermicron diameters, is key for understanding ice-nucleating particles (INPs). Supported by the Atmospheric Radiation Measurement (ARM) user facility, we sampled PM and surface soil materials at the Southern Great Plains observatory (SGP; 36° 36′ 18″ N, 97° 29′ 6″ W) to systematically compare the INP abundance and ice nucleation efficiency of different SGP samples (i.e., airborne versus surface materials). The field campaign, named Examing INP from SGP II (ExINP-SGP II), was conducted from 20 January to 20 April, 2021. Our data analysis products include (1) physical surface sorption characterization data (i.e., BET, pore volume) of two sets of samples -- SGP Soil and USDA, (2) X-ray diffraction spectra for the same two samples, (3) immersion freezing assay-based ice nucleation active mass density data as a function of freezing temperature for both ambient and surface samples, and (4) time-series data of ambient meteorological conditions, concentration particle counter-derived aerosol particle concentration, and aerosol particle sizer measurement during ExINP-SGP II.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Van Allen Probes observation and modeling of chorus excitation and propagation during weak geomagnetic activities

We report correlated data on nightside chorus waves and energetic electrons during two small storm periods: 1 November 2012 (Dst ≈ –45) and 14 January 2013 (Dst ≈ –18). The Van Allen Probes simultaneously observed strong chorus waves at locations L = 5.8 – 6.3, with a lower frequency band 0.1–0.5fce and a peak spectral density ~10 –4 nT 2 /Hz. In the same period, the fluxes and anisotropy of energetic (~10–300 keV) electrons were greatly enhanced in the interval of large negative interplanetary magnetic field Bz. Using a bi-Maxwellian distribution to model the observed electron distribution, we perform ray tracing simulations to show that nightside chorus waves are indeed produced by the observed electron distribution with a peak growth for a field-aligned propagation approximately between 0.3f ce and 0.4f ce , at latitude <7°. Moreover, chorus waves launched with initial normal angles either θ < 90° or > 90° propagate along the field either northward or southward and then bounce back either away from Earth for a lower frequency or toward Earth for higher frequencies. The current results indicate that nightside chorus waves can be excited even during weak geomagnetic activities in cases of continuous injection associated with negative Bz. Furthermore, we examine a dayside event during a small storm C on 8 May 2014 (Dst ≈ –45) and find that the observed anisotropic energetic electron distributions potentially contribute to the generation of dayside chorus waves, but this requires more thorough studies in the future.

58 GEOSCIENCES↗

DOE OSTI2014

Extrapolating active layer thickness measurements across Arctic polygonal terrain using LiDAR and NDVI data sets

Landscape attributes that vary with microtopography, such as active layer thickness (ALT), are labor intensive and difficult to document effectively through in situ methods at kilometer spatial extents, thus rendering remotely sensed methods desirable. Spatially explicit estimates of ALT can provide critically needed data for parameterization, initialization, and evaluation of Arctic terrestrial models. In this work, we demonstrate a new approach using high-resolution remotely sensed data for estimating centimeter-scale ALT in a 5 km 2 area of ice-wedge polygon terrain in Barrow, Alaska. We use a simple regression-based, machine learning data-fusion algorithm that uses topographic and spectral metrics derived from multisensor data (LiDAR and WorldView-2) to estimate ALT (2 m spatial resolution) across the study area. Comparison of the ALT estimates with ground-based measurements, indicates the accuracy (r 2 = 0.76, RMSE ±4.4 cm) of the approach. While it is generally accepted that broad climatic variability associated with increasing air temperature will govern the regional averages of ALT, consistent with prior studies, our findings using high-resolution LiDAR and WorldView-2 data, show that smaller-scale variability in ALT is controlled by local eco-hydro-geomorphic factors. This work demonstrates a path forward for mapping ALT at high spatial resolution and across sufficiently large regions for improved understanding and predictions of coupled dynamics among permafrost, hydrology, and land-surface processes from readily available remote sensing data.

58 GEOSCIENCES↗

DOE OSTI2013

Molecular radiotherapy: The NUKFIT software for calculating the time-integrated activity coefficient

Purpose: Calculation of the time-integrated activity coefficient (residence time) is a crucial step in dosimetry for molecular radiotherapy. However, available software is deficient in that it is either not tailored for the use in molecular radiotherapy and/or does not include all required estimation methods. The aim of this work was therefore the development and programming of an algorithm which allows for an objective and reproducible determination of the time-integrated activity coefficient and its standard error.Methods: The algorithm includes the selection of a set of fitting functions from predefined sums of exponentials and the choice of an error model for the used data. To estimate the values of the adjustable parameters an objective function, depending on the data, the parameters of the error model, the fitting function and (if required and available) Bayesian information, is minimized. To increase reproducibility and user-friendliness the starting values are automatically determined using a combination of curve stripping and random search. Visual inspection, the coefficient of determination, the standard error of the fitted parameters, and the correlation matrix are provided to evaluate the quality of the fit. The functions which are most supported by the data are determined using the corrected Akaike information criterion. The time-integrated activity coefficient is estimated by analytically integrating the fitted functions. Its standard error is determined assuming Gaussian error propagation. The software was implemented using MATLAB.Results: To validate the proper implementation of the objective function and the fit functions, the results of NUKFIT and SAAM numerical, a commercially available software tool, were compared. The automatic search for starting values was successfully tested for reproducibility. The quality criteria applied in conjunction with the Akaike information criterion allowed the selection of suitable functions. Function fit parameters and their standard error estimated by using SAAM numerical and NUKFIT showed differences of <1%. The differences for the time-integrated activity coefficients were also <1% (standard error between 0.4% and 3%). In general, the application of the software is user-friendly and the results are mathematically correct and reproducible. An application of NUKFIT is presented for three different clinical examples.Conclusions: The software tool with its underlying methodology can be employed to objectively and reproducibly estimate the time integrated activity coefficient and its standard error for most time activity data in molecular radiotherapy.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2019

Anti-Diabetic and Anti-Nephritic Activities of Grifola frondosa Mycelium Polysaccharides in Diet-Streptozotocin-Induced Diabetic Rats Via Modulation on Oxidative Stress

Grifola frondosa is an edible fungus with a variety of potential pharmacological activities. This study investigates the hypoglycemic, anti-diabetic nephritic, and antioxidant properties of G. frondosa polysaccharides in diet-streptozotocin-induced diabetic rats. After a 4-week treatment with 100 mg/kg of metformin and 200 mg/kg of one of four different G. frondosa polysaccharide mixtures (especially GFPS3 and GFPS4), diabetic rats had enhanced body weight and suppressed plasma glucose, indicating the hypoglycemic activities of the G. frondosa polysaccharides. G. frondosa polysaccharides regulated the level of serum creatinine, blood urea nitrogen, N-acetyl-β-D-glucosaminidase, and albuminuria; inhibited the serum levels of interleukin (IL)-2, IL-6, and TNF-α; and enhanced the serum levels of matrix metalloproteinase 9 and interferon-α, confirming their anti-diabetic nephritic activities. G. frondosa polysaccharides ameliorated the pathological alterations in the kidneys of diabetic rats. Moreover, G. frondosa polysaccharides modulated the serum levels of oxidant factors such as superoxide dismutase, glutathione peroxidase, catalase, malondialdehyde, and reactive oxygen species, revealing their antioxidant properties. Furthermore, the administration of G. frondosa polysaccharides inhibited nuclear factor kappa B activities in the serum and kidneys. All of the data revealed that the activation of nuclear factor kappa B plays a central role in G. frondosa polysaccharide-mediated anti-diabetic and anti-nephritic activities.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

AVTA Federal Fleet PEV Readiness Data Logging and Characterization Study for the National Park Service: Golden Gate National Recreation Area

Battelle Energy Alliance, LLC, managing and operating contractor for the U.S. Department of Energy's Idaho National Laboratory, is the lead laboratory for U.S. Department of Energy Advanced Vehicle Testing. Battelle Energy Alliance, LLC contracted with Intertek Testing Services, North America (ITSNA) to collect data on federal fleet operations as part of the Advanced Vehicle Testing Activity's Federal Fleet Vehicle Data Logging and Characterization study. The Advanced Vehicle Testing Activity study seeks to collect data to validate the utilization of advanced electric drive vehicle transportation. This report focuses on the Golden Gate National Recreation Area (GGNRA) fleet to identify daily operational characteristics of select vehicles and report findings on vehicle and mission characterizations to support the successful introduction of plug-in electric vehicles (PEVs) into the agencies' fleets. Individual observations of these selected vehicles provide the basis for recommendations related to electric vehicle adoption and whether a battery electric vehicle or plug-in hybrid electric vehicle (PHEV) (collectively PEVs) can fulfill the mission requirements. GGNRA identified 182 vehicles in its fleet, which are under the management of the U.S. General Services Administration. Fleet vehicle mission categories are defined in Section 4, and while the GGNRA vehicles conduct many different missions, only two (i.e., support and law enforcement missions) were selected by agency management to be part of this fleet evaluation. The selected vehicles included sedans, trucks, and sport-utility vehicles. This report will show that battery electric vehicles and/or PHEVs are capable of performing the required missions and providing an alternative vehicle for support vehicles and PHEVs provide the same for law enforcement, because each has a sufficient range for individual trips and time is available each day for charging to accommodate multiple trips per day. These charging events could occur at the vehicle home base, high-use work areas, or intermediately along routes that the vehicles frequently travel. Replacement of vehicles in the current fleet would result in significant reductions in the emission of greenhouse gases and petroleum use, while also reducing fuel costs. The San Francisco Bay Area is a leader in the adoption of PEVs in the United States. PEV charging stations, or more appropriately identified as electric vehicle supply equipment, located on the GGNRA facility would be a benefit for both GGNRA fleets and general public use. Fleet drivers and park visitors operating privately owned PEVs benefit by using the charging infrastructure. ITSNA recommends location analysis of the GGNRA site to identify the optimal placement of the electric vehicle supply equipment station. ITSNA recognizes the support of Idaho National Laboratory and ICF International for their efforts to initiate communication with the National Parks Service and GGNRA for participation in the study. ITSNA is pleased to provide this report and is encouraged by the high interest and support from the National Park Service and GGNRA personnel.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2014

AVTA Federal Fleet PEV Readiness Data Logging and Characterization Study for the National Park Service: Fort Vancouver National Historic Site

Battelle Energy Alliance, LLC, managing and operating contractor for the U.S. Department of Energy’s Idaho National Laboratory, is the lead laboratory for the U.S. Department of Energy’s Advanced Vehicle Testing. Battelle Energy Alliance, LLC contracted with Intertek Testing Services, North America (ITSNA) to collect data on federal fleet operations as part of the Advanced Vehicle Testing Activity’s Federal Fleet Vehicle Data Logging and Characterization study. The Advanced Vehicle Testing Activity study seeks to collect data to validate the use of advanced electric drive vehicle transportation.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2014

Damsel - A Data Model Storage Library for Exascale Science

The goal of this project is to enable exascale computational science applications to interact conveniently and efficiently with storage through abstractions that match their data models. We will accomplish this through three major activities: (1) identifying major data model motifs in computational science applications and developing representative benchmarks; (2) developing a data model storage library, called Damsel, that supports these motifs, provides efficient storage data layouts, incorporates optimizations to enable exascale operation, and is tolerant to failures; and (3) productizing Damsel and working with computational scientists to encourage adoption of this library by the scientific community.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

Damsel: A Data Model Storage Library for Exascale Science

The goal of this project is to enable exascale computational science applications to interact conveniently and efficiently with storage through abstractions that match their data models. We will accomplish this through three major activities: (1) identifying major data model motifs in computational science applications and developing representative benchmarks; (2) developing a data model storage library, called Damsel, that supports these motifs, provides efficient storage data layouts, incorporates optimizations to enable exascale operation, and is tolerant to failures; and (3) productizing Damsel and working with computational scientists to encourage adoption of this library by the scientific community.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Malicious Cyber Activity Detection using Zigzag Persistence

In this study we synthesize zigzag persistence from topological data analysis with autoencoder-based approaches to detect malicious cyber activity, and derive analytic insights. Cybersecurity aims to safeguard computers, networks, and servers from various forms of malicious attacks, including network damage, data theft, and activity monitoring. We focus on the cybersecurity domain and investigate the detection of malicious activity using log data. We consider the dynamics of the log data and explore the changing topology of a hypergraph representation of this data to gain insights into the underlying activity. These hypergraphs capture complex interactions between processes, together with their temporal information. To study the changing topology we use zigzag persistence, which captures how topological features persist at multiple dimensions over time. We observe that this detects malicious activity in a cyber data set. To automate this detection we implement an autoencoder trained on a vectorization of the resulting zigzag persistence barcodes. Our experimental results demonstrate the effectiveness of the autoencoder in detecting malicious activity. Overall, this study highlights the potential of zigzag persistence and its combination with temporal hypergraphs for analyzing cybersecurity log data and detecting malicious behavior.

hypergraphs, temporal hypergraph, topological data↗

DOE OSTI2026

Concerted Proton–Electron Transfer Minimizes Substituent Effects on Adsorbed Phthalocyanine Electrocatalysis

Molecularly modified electrodes (MMEs) are potent electrocatalysts, but few principles exist for their rational design. Electrocatalysis by soluble molecules depends strongly on substituents that tune the catalyst redox potential (E 1/2 ), but it is unclear if this parameter similarly impacts MME catalysis. Herein, we employ the hydrogen evolution reaction (HER) as a test case for comparing carbon-adsorbed cobalt phthalocyanine (CoPc/C) and cobalt hexadecafluoro-phthalocyanine (CoFPc/C). By correlating HER activity and voltammetric data to total Co surface concentration across a wide range of catalyst loadings, we find that only 5–25% of adsorbed Co sites contribute to the Co(II/I) redox wave and that this subpopulation poorly correlates with catalytic activity. Instead, in the low-loading limit, catalytic activity correlates linearly with the majority Co(II/I)-silent Co population, revealing per-site turnover frequency (TOF) values for HER. Despite a 230 mV difference in Co(II/I) redox potentials, CoPc/C and CoFPc/C display TOF values differing by less than a factor of 3 when compared over a wide potential range. Mechanistic studies point to an inner-sphere concerted proton–electron transfer step as rate-determining, suggesting that the Co–H bond dissociation free energy (BDFE) rather than the Co(II/I) E 1/2 is thermodynamically relevant. Computational studies indicate that the fluoro-substituents lead to compensatory changes in Co(II/I) E 1/2 and Co(I) basicity, leaving the Co–H BDFE largely unchanged between CoPc and CoFPc and thereby manifesting in similar catalytic rates. Furthermore, these results highlight the limited effect of E 1/2 -tuning on MME catalytic activity and motivate the development of methods to directly alter active site–substrate BDFE.

Catalysts↗

DOE OSTI2025

Modeling household-level party composition behavior for multiparty activities: a random parameter nested logit modeling approach

This study presents findings of a household-level party composition model for multiparty activities. It exploits data from a comprehensive Household Travel Survey conducted by Chicago Metropolitan Agency of Planning. The study estimates a random parameter nested logit model to capture households’ unobserved preference heterogeneity and non-proportional substitution patterns in terms of activity party composition for multiparty activities. A wide variety of household demographics, activity attributes and residential neighborhood characteristics are examined in this paper. The magnitude of the impacts of the determinants are tested in this study by analyzing the elasticity of the variables, which suggests that household demographics and attributes of the multiparty activities have significant effects on the household-level activity party composition. Residential neighborhood characteristics, although somewhat less impactful, still play a meaningful role. This model will be implemented within the POLARIS transportation systems simulator to improve the activity generation modeling workflow, and the prediction accuracy of various activity-travel components.

activity party composition↗

DOE OSTI2018

Isopiestic measurements of thermodynamic properties for the aqueous system LiBr–CaBr 2 –H 2 O at 373.15 K

In this study, the isopiestic molalities for the systems LiBr–H 2 O, CaBr 2 –H 2 O and LiBr–CaBr 2 –H 2 O were measured at 373.15 K with the isopiestic method using the Oak Ridge National Laboratory (ORNL) high–temperature gravimetric isopiestic apparatus. The osmotic coefficients were determined based on the lithium chloride and sodium chloride reference standards. The vapor pressure diagrams and osmotic coefficient diagrams at different mole fraction for LiBr were plotted. The calculated vapor pressure with water activities agree well with the experimental data. On the basis of Pitzer original and its extended model, the Pitzer binary parameters β (0) , β (1) C (0) and C (1) for the systems LiBr–H 2 O and CaBr 2 –H 2 O and mixing parameters of θ Li,Ca and ψ Li,Ca,Br were fitted with the measured osmotic coefficients. The calculated osmotic coefficients for systems LiBr–H 2 O and CaBr 2 –H 2 O agree well with the experimental data. The agreement between the calculated water activities and experimental results for the ternary system indicates that the parameters obtained in this work are reliable for water activity calculation. Finally, the thermodynamic data obtained in this study are essential for development of universal thermodynamic models for brine systems containing lithium bromide and calcium bromide.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Microtopographic and Depth Controls on Active Layer Chemistry in Arctic Polygonal Ground: Supporting Data

Polygonal ground is a signature characteristic of the Arctic, and permafrost thaw can potentially generate substantial feedbacks to Arctic ecosystems and climate. This study describes the first comprehensive spatial examination of active layer biogeochemistry that extends across high- and low-centered polygons and their features, including depth. Water chemistry measurements were made on active layer water samples collected near Barrow, Alaska during summer, 2012. Several significant differences in chemistry were observed between high- and low-centered polygons suggesting polygon types may be useful for landscape-scale geochemical classification. However, differences were found for polygon features (centers and troughs) for analytes that were not significant for type, suggesting that finer scale features control biogeochemistry in a different way than polygon type. Depth variations were also significant, demonstrating important multi-dimensional aspects of polygonal ground biogeochemistry. These results have major implications for understanding how polygonal ground ecosystems function, and how they may respond to future change. This data package includes one *.csv data file and one *.pdf user guide. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗